Absence or impairment of functional communication is a fundamental deficit in Autism Spectrum Disorder (ASD). The specific factors that contribute to a great variety of speech and language impairments are still unknown but have a neurobiological substratum. We investigated the brain control of speech production mechanism in children with ASD using Magnetoencephalography (MEG). MEG is a neuroimaging modality with high temporal resolution that records neural activation in real time. A group of children with ASD and age- and sex- matched controls performed simple oromotor (open and close mouth) and speech tasks (one-syllable and multi-syllable phoneme production). Atypical and significantly different brain neural activation in motor (BA 6 and BA 4) areas and speech control (BA 47, BA 22) areas were noted in children with ASD compared to typically developing controls. The present thesis provides new evidence contributing to the understanding of speech and language production in individuals with autism.

No description available.

Catechol-O-methyltransferase (COMT) metabolizes catechols, notably dopamine. The COMT Val158Met polymorphism influences its enzyme activity, and multiple neural correlates of this genotype on dopaminergic phenotypes have been reported, particularly with regards to working memory. COMT activity can also be regulated pharmacologically by COMT inhibitors. The ‘inverted-U’ relationship between dopamine signalling and cognitive performance predicts that the effects of COMT inhibition will differ according to COMT genotype. The goal of this thesis was to better understand COMT’s impact on brain function and behaviour. Here, 33 subjects homozygous for COMT Val158 (‘Val homozygotes’) and 34 homozygous for COMT Met158 (‘Met homozygotes’) were randomly assigned, double-blind, to a single dose of the brain-penetrant COMT inhibitor tolcapone (200mg) or placebo. They completed the N-back task of working memory, an emotional face processing task, and a gambling task, in a magnetoencephalography (MEG) scanner, allowing both behavioural performance and neural activity to be investigated. The data presented in this thesis confirm that COMT activity influences performance on, and neural activity during, the N-back task, in a way consistent with the inverted-U model of dopamine function. The effect on risky decision making is novel, and indicates that COMT plays roles in domains beyond working memory, and that such domains may also follow an inverted-U. Neural activity during the faces task and the gambling task also show COMT-modulated differences. The behavioural results show that the direction of effect of a drug can be influenced by sequence variation in its target gene. They are of translational relevance, since COMT inhibitors are used in the adjunctive treatment of Parkinson’s disease and are under evaluation in schizophrenia and other disorders. The MEG data show that for the three tasks, there are effects of Val158Met genotype, of tolcapone, and their interaction, on neural activity (for example, the P300 during N-back), revealing a complex temporal and spatial pattern which sheds some light on the neural processing underlying these tasks and their previously reported fMRI correlates.

A Neuroimagem Funcional evoluiu muito nos últimos anos com o aparecimento de técnicas como Positron Emission Tomography ou PET (Tomógrafo por Emissão de Pósitrons) e Functional Magnetic Ressonance Image ou fMRI (Imagem de RessonÂncia Magnética Funcional) [Belliveau et al., 1991]. Elas permitem a observação de atividade no cérebro com uma resolução de alguns milímetros, e devido a natureza do sinal medido, com uma resolução temporal da ordem de 5 segundos [Kim et al., 1997]. Magnetoencefalografia e Eletroencefalografia (M/EEG), por outro lado, possuem uma resoluçao temporal da ordem de milissegundos, já que o sinal é produzido pela movimentação do íons através das membranas celulares [Nunez and Srinivasan, 2006]. Porém a sua resoluçeo espacial é muito baixa jé que tipicamente são problemas mal postos, com muito mais variáveis do que dados. Um equipamento de M/EEG de alta resolução possui da ordem de O(200) canais, que permitem medidas do campo magnético (para o MEG) ou do potencial elétrico (para o EEG) em O(200) posições em torno da cabeça. Para uma escala com resolução de ordem l existem (L /l )3 variáveis, onde L = aprox. 15cm. Neste trabalho procuramos estudar métodos para aumentar a resolução espacial das técnicas de EEG, pois o mapeamento funcional do cérebro humano esta intimamente relacionado à localização da atividade no espaço bem como no tempo [Friston, 2009] (muitas relativo ao momento de um estímulo externo). Todo o trabalho de localização de fontes para EEG pode ser facilmente estendido para MEG. Métodos Bayesianos são o cenário natural para lidar com problemas mal postos [Wipf and Nagarajan, 2009]. Existem, essencialmente, duas direções nas quais os algoritmos Bayesianos podem ser melhoradas, através da construção de uma melhor verossimilhança ou uma distribuição a Priori. Embora reconheçamos que avanços importantes podem ser feitos no direção anterior, aqui nos concentramos na segunda. Neste trabalho nós introduzimos um método multiescala para construir uma melhor distribuição a Priori. Uma idéia similar foi estudada dentro do contexto mais simples de fMRI [Amaral et al., 2004]. Muitos novos problemas aparecem ao lidar com o caráter vetorial do EEG. O mais importante, é a construção de um conjunto de superfícies renormalizadas que aproximam a região cortical onde a fonte de atividade esta localizada e o problema relacionado de de nir as variáveis relevantes para representar o cérebro em uma escala com menor resolução. A validação do novo algoritmo é sempre um problema essencial. Nós apresentamos resultados que sugerem, em dados simulados, que nosso método pode ser uma alternativa válida para os atuais algoritmos, julgando ambos pela taxa de erros na localização de fontes bem como pelo tempo que eles levam para convergir. / Functional Neuroimaging has evolved in the last few decades with the introduction of techniques such as Positron Emission Tomography or PET and Functional Magnetic Ressonance Image or fMRI [Belliveau et al., 1991]. These allow observing brain activity with a resolution of a few millimeters and, due to the nature of the signal, a time resolution of the order of 5 seconds [Kim et al., 1997]. M/EEG, on the other hand, have a millisecond time resolution, since the signal is produced by the transport of ions through cell membranes [Nunez and Srinivasan, 2006]. However their space resolution is much lower since these are typically ill posed problems with many more unknowns than data points. A high resolution M/EEG has of the order of O(200) data channels, which allow measuring the magnetic or electric field at O(200) positions around the head. For a resolution scale of order l there are O(L l )3 variables, where L = 15cm. In this work we aim at studying methods to increase the spatial resolution of EEG techniques, since functional mapping of the human brain is intimately related to the localization of the activity in space as well as in time [Friston, 2009] (often relative to the time of external stimuli). Any advance in the inverse problem of source localization for EEG can rather easily be extended to deal with MEG. Bayesian methods are the natural setting to deal with ill posed problems [Wipf and Nagarajan, 2009]. There are essentially two directions in which Bayesian algorithms can be improved, by building a better likelihood or a prior distribution. While we recognize that important advances can be done in the former direction we here concentrate in the latter. In this work we introduce a multiscale method to build an improved prior distribution. A similar idea has been studied within an easier context of fMRI [Amaral et al., 2004]. Several new problems appear in dealing with the vectorial character of EEG. The most important, is the construction of a set of renormalized lattices that approximate the cortex region where the source activity is located and the related problem of de ning the relevant variables in coarser scale representation of the cortex. Validation of a new algorithm is always an essential problem. We present results which suggest on simulated data, that our method might be a valid alternative to current algorithms, judged both by the rate of errors in source localization as well as by the time it takes to converge.

This study evaluated a time-restricted region-suppressed event-related synthetic aperture magnetoencephalography (TRRS-ER-SAM) beamformer algorithm against equivalent current dipole (ECD), and event-related synthetic aperture magnetoencephalography (ER-SAM) post-processing methods for magnetoencephalography data. This evaluation was done numerically and with auditory evoked field (AEF) data elicited by binaurally presented 500 Hz tones. The TRRS-ER-SAM beamformer demonstrated robustness to noise, and the ability to handle coherent sources. The TRRS-ER-SAM algorithm was then applied to a study of N1m AEFs in 8 subjects aged 12-25 years. The study examined the effects of age, stimulus frequency, and right-sided monaural versus binaural stimulation on the N1m location, amplitude, and latency. It was found that age affected the N1m latency; stimulus frequency affected the N1m location, amplitude, and latency; and monaural versus binaural stimulation affected the N1m amplitude. In the context of these effects, the auditory pathway structure and neurophysiological changes due to maturation were discussed.

This study evaluated a time-restricted region-suppressed event-related synthetic aperture magnetoencephalography (TRRS-ER-SAM) beamformer algorithm against equivalent current dipole (ECD), and event-related synthetic aperture magnetoencephalography (ER-SAM) post-processing methods for magnetoencephalography data. This evaluation was done numerically and with auditory evoked field (AEF) data elicited by binaurally presented 500 Hz tones. The TRRS-ER-SAM beamformer demonstrated robustness to noise, and the ability to handle coherent sources. The TRRS-ER-SAM algorithm was then applied to a study of N1m AEFs in 8 subjects aged 12-25 years. The study examined the effects of age, stimulus frequency, and right-sided monaural versus binaural stimulation on the N1m location, amplitude, and latency. It was found that age affected the N1m latency; stimulus frequency affected the N1m location, amplitude, and latency; and monaural versus binaural stimulation affected the N1m amplitude. In the context of these effects, the auditory pathway structure and neurophysiological changes due to maturation were discussed.

With MEG, the tiny magnetic fields produced by neuronal currents within the brain can be measured completely non-invasively. But the signals are very small (~100 fT) and often obscured by spontaneous brain activity and external noise. So, a recurrent issue in MEG data analysis is the identification and elimination of this unwanted interference within the recordings. Various strategies exist to meet this purpose. In this thesis, two of these strategies are scrutinized in detail. The first is the commonly used procedure of averaging over trials which is a successfully applied data reduction method in many neurocognitive studies. However, the brain does not always respond identically to repeated stimuli, so averaging can eliminate valuable information. Alternative approaches aiming at single trial analysis are difficult to realize and many of them focus on temporal patterns. Here, a compromise involving random subaveraging of trials and repeated source localization is presented. A simulation study with numerous examples demonstrates the applicability of the new method. As a result, inferences about the generators of single trials can be drawn which allows deeper insight into neuronal processes of the human brain. The second technique examined in this thesis is a preprocessing tool termed Signal Space Separation (SSS). It is widely used for preprocessing of MEG data, including noise reduction by suppression of external interference, as well as movement correction. Here, the mathematical principles of the SSS series expansion and the rules for its application are investigated. The most important mathematical precondition is a source-free sensor space. Using three data sets, the influence of a violation of this convergence criterion on source localization accuracy is demonstrated. The analysis reveals that the SSS method works reliably, even when the convergence criterion is not fully obeyed. This leads to utilizing the SSS method for the transformation of MEG data to virtual sensors on the scalp surface. Having MEG data directly on the individual scalp surface would alleviate sensor space analysis across subjects and comparability with EEG. A comparison study of the transformation results obtained with SSS and those produced by inverse and subsequent forward computation is performed. It shows strong dependence on the relative position of sources and sensors. In addition, the latter approach yields superior results for the intended purpose of data transformation.

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 100-110). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 100-110). Also available on the Internet.

Background: Isometric handgrip (IHG) exercise increases heart rate (HR) and mean arterial pressure (MAP); MAP can be sustained after exercise via post-exercise ischemia (PEI). HR and MAP responses are mediated by feed-forward cortical signals (central command, CC) and neural feedback from active muscles (exercise pressor reflex, EPR). Purpose: Differentiate between cortical regions involved with CC versus the EPR via changes in alpha (8-12Hz) and beta (13-30Hz) power using magnetoencephalography (MEG). Methods: Participants (n=11, 22 ± 2 years) completed a repeated IHG and PEI protocol at 5% (control) and 40% maximum force. Results: HR and MAP increased (p<0.04) early during IHG (CC only), while MAP increased further (p=0.03) as IHG continued (CC & EPR). The MAP response persisted during PEI (EPR, p=0.07). During IHG, alpha and beta power decreased within the contralateral sensorimotor cortex. Power increased within MEG sensors associated with the ipsilateral (IHG-alpha) and contralateral (IHG-beta and PEI-beta) insular cortex.